This paper tries to identify rules and factors that are
predictive for the outcome of international conflict management
attempts. We use C4.5, an advanced Machine Learning algorithm, for
generating decision trees and prediction rules from cases in the
CONFMAN database. The results show that simple patterns and rules are
often not only more understandable, but also more reliable than
complex rules. Simple decision trees are able to improve the chances
of correctly predicting the outcome of a conflict management
attempt. This suggests that mediation is more repetitive than
conflicts per se, where such results have not been achieved so far.